{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "keras_04_mnist_convolutional.ipynb",
      "version": "0.3.2",
      "provenance": [],
      "collapsed_sections": [],
      "toc_visible": true,
      "include_colab_link": true
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.5.3"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/GoogleCloudPlatform/tensorflow-without-a-phd/blob/master/tensorflow-mnist-tutorial/keras_04_mnist_convolutional.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "Lvo0t7XVIkWZ"
      },
      "source": [
        "### Parameters"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "cCpkS9C_H7Tl",
        "colab": {}
      },
      "source": [
        "BATCH_SIZE = 128\n",
        "EPOCHS = 10\n",
        "\n",
        "training_images_file   = 'gs://mnist-public/train-images-idx3-ubyte'\n",
        "training_labels_file   = 'gs://mnist-public/train-labels-idx1-ubyte'\n",
        "validation_images_file = 'gs://mnist-public/t10k-images-idx3-ubyte'\n",
        "validation_labels_file = 'gs://mnist-public/t10k-labels-idx1-ubyte'"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "qpiJj8ym0v0-"
      },
      "source": [
        "### Imports"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "AoilhmYe1b5t",
        "outputId": "167b0893-ab0b-4179-b28b-6a5edc480956",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "import os, re, math, json, shutil, pprint\n",
        "import PIL.Image, PIL.ImageFont, PIL.ImageDraw\n",
        "import IPython.display as display\n",
        "import numpy as np\n",
        "import tensorflow as tf\n",
        "from matplotlib import pyplot as plt\n",
        "tf.enable_eager_execution()\n",
        "print(\"Tensorflow version \" + tf.__version__)"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Tensorflow version 1.14.0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "cellView": "form",
        "colab_type": "code",
        "id": "qhdz68Xm3Z4Z",
        "colab": {}
      },
      "source": [
        "#@title visualization utilities [RUN ME]\n",
        "\"\"\"\n",
        "This cell contains helper functions used for visualization\n",
        "and downloads only. You can skip reading it. There is very\n",
        "little useful Keras/Tensorflow code here.\n",
        "\"\"\"\n",
        "\n",
        "# Matplotlib config\n",
        "plt.ioff()\n",
        "plt.rc('image', cmap='gray_r')\n",
        "plt.rc('grid', linewidth=1)\n",
        "plt.rc('xtick', top=False, bottom=False, labelsize='large')\n",
        "plt.rc('ytick', left=False, right=False, labelsize='large')\n",
        "plt.rc('axes', facecolor='F8F8F8', titlesize=\"large\", edgecolor='white')\n",
        "plt.rc('text', color='a8151a')\n",
        "plt.rc('figure', facecolor='F0F0F0', figsize=(16,9))\n",
        "# Matplotlib fonts\n",
        "MATPLOTLIB_FONT_DIR = os.path.join(os.path.dirname(plt.__file__), \"mpl-data/fonts/ttf\")\n",
        "\n",
        "# pull a batch from the datasets. This code is not very nice, it gets much better in eager mode (TODO)\n",
        "def dataset_to_numpy_util(training_dataset, validation_dataset, N):\n",
        "  \n",
        "  # get one batch from each: 10000 validation digits, N training digits\n",
        "  batch_train_ds = training_dataset.apply(tf.data.experimental.unbatch()).batch(N)\n",
        "  \n",
        "  # eager execution: loop through datasets normally\n",
        "  if tf.executing_eagerly():\n",
        "    for validation_digits, validation_labels in validation_dataset:\n",
        "      validation_digits = validation_digits.numpy()\n",
        "      validation_labels = validation_labels.numpy()\n",
        "      break\n",
        "    for training_digits, training_labels in batch_train_ds:\n",
        "      training_digits = training_digits.numpy()\n",
        "      training_labels = training_labels.numpy()\n",
        "      break\n",
        "    \n",
        "  else:\n",
        "    v_images, v_labels = validation_dataset.make_one_shot_iterator().get_next()\n",
        "    t_images, t_labels = batch_train_ds.make_one_shot_iterator().get_next()\n",
        "    # Run once, get one batch. Session.run returns numpy results\n",
        "    with tf.Session() as ses:\n",
        "      (validation_digits, validation_labels,\n",
        "       training_digits, training_labels) = ses.run([v_images, v_labels, t_images, t_labels])\n",
        "  \n",
        "  # these were one-hot encoded in the dataset\n",
        "  validation_labels = np.argmax(validation_labels, axis=1)\n",
        "  training_labels = np.argmax(training_labels, axis=1)\n",
        "  \n",
        "  return (training_digits, training_labels,\n",
        "          validation_digits, validation_labels)\n",
        "\n",
        "# create digits from local fonts for testing\n",
        "def create_digits_from_local_fonts(n):\n",
        "  font_labels = []\n",
        "  img = PIL.Image.new('LA', (28*n, 28), color = (0,255)) # format 'LA': black in channel 0, alpha in channel 1\n",
        "  font1 = PIL.ImageFont.truetype(os.path.join(MATPLOTLIB_FONT_DIR, 'DejaVuSansMono-Oblique.ttf'), 25)\n",
        "  font2 = PIL.ImageFont.truetype(os.path.join(MATPLOTLIB_FONT_DIR, 'STIXGeneral.ttf'), 25)\n",
        "  d = PIL.ImageDraw.Draw(img)\n",
        "  for i in range(n):\n",
        "    font_labels.append(i%10)\n",
        "    d.text((7+i*28,0 if i<10 else -4), str(i%10), fill=(255,255), font=font1 if i<10 else font2)\n",
        "  font_digits = np.array(img.getdata(), np.float32)[:,0] / 255.0 # black in channel 0, alpha in channel 1 (discarded)\n",
        "  font_digits = np.reshape(np.stack(np.split(np.reshape(font_digits, [28, 28*n]), n, axis=1), axis=0), [n, 28*28])\n",
        "  return font_digits, font_labels\n",
        "\n",
        "# utility to display a row of digits with their predictions\n",
        "def display_digits(digits, predictions, labels, title, n):\n",
        "  fig = plt.figure(figsize=(13,3))\n",
        "  digits = np.reshape(digits, [n, 28, 28])\n",
        "  digits = np.swapaxes(digits, 0, 1)\n",
        "  digits = np.reshape(digits, [28, 28*n])\n",
        "  plt.yticks([])\n",
        "  plt.xticks([28*x+14 for x in range(n)], predictions)\n",
        "  plt.grid(b=None)\n",
        "  for i,t in enumerate(plt.gca().xaxis.get_ticklabels()):\n",
        "    if predictions[i] != labels[i]: t.set_color('red') # bad predictions in red\n",
        "  plt.imshow(digits)\n",
        "  plt.grid(None)\n",
        "  plt.title(title)\n",
        "  display.display(fig)\n",
        "  \n",
        "# utility to display multiple rows of digits, sorted by unrecognized/recognized status\n",
        "def display_top_unrecognized(digits, predictions, labels, n, lines):\n",
        "  idx = np.argsort(predictions==labels) # sort order: unrecognized first\n",
        "  for i in range(lines):\n",
        "    display_digits(digits[idx][i*n:(i+1)*n], predictions[idx][i*n:(i+1)*n], labels[idx][i*n:(i+1)*n],\n",
        "                   \"{} sample validation digits out of {} with bad predictions in red and sorted first\".format(n*lines, len(digits)) if i==0 else \"\", n)\n",
        "\n",
        "def plot_learning_rate(lr_func, epochs):\n",
        "  xx = np.arange(epochs+1, dtype=np.float)\n",
        "  y = [lr_decay(x) for x in xx]\n",
        "  fig, ax = plt.subplots(figsize=(9, 6))\n",
        "  ax.set_xlabel('epochs')\n",
        "  ax.set_title('Learning rate\\ndecays from {:0.3g} to {:0.3g}'.format(y[0], y[-2]))\n",
        "  ax.minorticks_on()\n",
        "  ax.grid(True, which='major', axis='both', linestyle='-', linewidth=1)\n",
        "  ax.grid(True, which='minor', axis='both', linestyle=':', linewidth=0.5)\n",
        "  ax.step(xx,y, linewidth=3, where='post')\n",
        "  display.display(fig)\n",
        "\n",
        "class PlotTraining(tf.keras.callbacks.Callback):\n",
        "  def __init__(self, sample_rate=1, zoom=1):\n",
        "    self.sample_rate = sample_rate\n",
        "    self.step = 0\n",
        "    self.zoom = zoom\n",
        "    self.steps_per_epoch = 60000//BATCH_SIZE\n",
        "\n",
        "  def on_train_begin(self, logs={}):\n",
        "    self.batch_history = {}\n",
        "    self.batch_step = []\n",
        "    self.epoch_history = {}\n",
        "    self.epoch_step = []\n",
        "    self.fig, self.axes = plt.subplots(1, 2, figsize=(16, 7))\n",
        "    plt.ioff()\n",
        "\n",
        "  def on_batch_end(self, batch, logs={}):\n",
        "    if (batch % self.sample_rate) == 0:\n",
        "      self.batch_step.append(self.step)\n",
        "      for k,v in logs.items():\n",
        "        # do not log \"batch\" and \"size\" metrics that do not change\n",
        "        # do not log training accuracy \"acc\"\n",
        "        if k=='batch' or k=='size':# or k=='acc':\n",
        "          continue\n",
        "        self.batch_history.setdefault(k, []).append(v)\n",
        "    self.step += 1\n",
        "\n",
        "  def on_epoch_end(self, epoch, logs={}):\n",
        "    plt.close(self.fig)\n",
        "    self.axes[0].cla()\n",
        "    self.axes[1].cla()\n",
        "      \n",
        "    self.axes[0].set_ylim(0, 1.2/self.zoom)\n",
        "    self.axes[1].set_ylim(1-1/self.zoom/2, 1+0.1/self.zoom/2)\n",
        "    \n",
        "    self.epoch_step.append(self.step)\n",
        "    for k,v in logs.items():\n",
        "      # only log validation metrics\n",
        "      if not k.startswith('val_'):\n",
        "        continue\n",
        "      self.epoch_history.setdefault(k, []).append(v)\n",
        "\n",
        "    display.clear_output(wait=True)\n",
        "    \n",
        "    for k,v in self.batch_history.items():\n",
        "      self.axes[0 if k.endswith('loss') else 1].plot(np.array(self.batch_step) / self.steps_per_epoch, v, label=k)\n",
        "      \n",
        "    for k,v in self.epoch_history.items():\n",
        "      self.axes[0 if k.endswith('loss') else 1].plot(np.array(self.epoch_step) / self.steps_per_epoch, v, label=k, linewidth=3)\n",
        "      \n",
        "    self.axes[0].legend()\n",
        "    self.axes[1].legend()\n",
        "    self.axes[0].set_xlabel('epochs')\n",
        "    self.axes[1].set_xlabel('epochs')\n",
        "    self.axes[0].minorticks_on()\n",
        "    self.axes[0].grid(True, which='major', axis='both', linestyle='-', linewidth=1)\n",
        "    self.axes[0].grid(True, which='minor', axis='both', linestyle=':', linewidth=0.5)\n",
        "    self.axes[1].minorticks_on()\n",
        "    self.axes[1].grid(True, which='major', axis='both', linestyle='-', linewidth=1)\n",
        "    self.axes[1].grid(True, which='minor', axis='both', linestyle=':', linewidth=0.5)\n",
        "    display.display(self.fig)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "Lz1Zknfk4qCx"
      },
      "source": [
        "### tf.data.Dataset: parse files and prepare training and validation datasets\n",
        "Please read the [best practices for building](https://www.tensorflow.org/guide/performance/datasets) input pipelines with tf.data.Dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "ZE8dgyPC1_6m",
        "colab": {}
      },
      "source": [
        "AUTO = tf.data.experimental.AUTOTUNE\n",
        "\n",
        "def read_label(tf_bytestring):\n",
        "    label = tf.decode_raw(tf_bytestring, tf.uint8)\n",
        "    label = tf.reshape(label, [])\n",
        "    label = tf.one_hot(label, 10)\n",
        "    return label\n",
        "  \n",
        "def read_image(tf_bytestring):\n",
        "    image = tf.decode_raw(tf_bytestring, tf.uint8)\n",
        "    image = tf.cast(image, tf.float32)/256.0\n",
        "    image = tf.reshape(image, [28*28])\n",
        "    return image\n",
        "  \n",
        "def load_dataset(image_file, label_file):\n",
        "    imagedataset = tf.data.FixedLengthRecordDataset(image_file, 28*28, header_bytes=16)\n",
        "    imagedataset = imagedataset.map(read_image, num_parallel_calls=16)\n",
        "    labelsdataset = tf.data.FixedLengthRecordDataset(label_file, 1, header_bytes=8)\n",
        "    labelsdataset = labelsdataset.map(read_label, num_parallel_calls=16)\n",
        "    dataset = tf.data.Dataset.zip((imagedataset, labelsdataset))\n",
        "    return dataset \n",
        "  \n",
        "def get_training_dataset(image_file, label_file, batch_size):\n",
        "    dataset = load_dataset(image_file, label_file)\n",
        "    dataset = dataset.cache()  # this small dataset can be entirely cached in RAM, for TPU this is important to get good performance from such a small dataset\n",
        "    dataset = dataset.shuffle(5000, reshuffle_each_iteration=True)\n",
        "    dataset = dataset.repeat() # Mandatory for Keras for now\n",
        "    dataset = dataset.batch(batch_size, drop_remainder=True) # drop_remainder is important on TPU, batch size must be fixed\n",
        "    dataset = dataset.prefetch(AUTO)  # fetch next batches while training on the current one (-1: autotune prefetch buffer size)\n",
        "    return dataset\n",
        "  \n",
        "def get_validation_dataset(image_file, label_file):\n",
        "    dataset = load_dataset(image_file, label_file)\n",
        "    dataset = dataset.cache() # this small dataset can be entirely cached in RAM, for TPU this is important to get good performance from such a small dataset\n",
        "    dataset = dataset.batch(10000, drop_remainder=True) # 10000 items in eval dataset, all in one batch\n",
        "    dataset = dataset.repeat() # Mandatory for Keras for now\n",
        "    return dataset\n",
        "\n",
        "# instantiate the datasets\n",
        "training_dataset = get_training_dataset(training_images_file, training_labels_file, BATCH_SIZE)\n",
        "validation_dataset = get_validation_dataset(validation_images_file, validation_labels_file)\n",
        "\n",
        "# For TPU, we will need a function that returns the dataset\n",
        "training_input_fn = lambda: get_training_dataset(training_images_file, training_labels_file, BATCH_SIZE)\n",
        "validation_input_fn = lambda: get_validation_dataset(validation_images_file, validation_labels_file)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "_fXo6GuvL3EB"
      },
      "source": [
        "### Let's have a look at the data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "yZ4tjPKvL2eh",
        "outputId": "f69b308a-3ceb-445d-aeee-1fcef36b3bb5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 177
        }
      },
      "source": [
        "N = 24\n",
        "(training_digits, training_labels,\n",
        " validation_digits, validation_labels) = dataset_to_numpy_util(training_dataset, validation_dataset, N)\n",
        "display_digits(training_digits, training_labels, training_labels, \"training digits and their labels\", N)\n",
        "display_digits(validation_digits[:N], validation_labels[:N], validation_labels[:N], \"validation digits and their labels\", N)\n",
        "font_digits, font_labels = create_digits_from_local_fonts(N)"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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+It90dHQkR0dHSk5OVllunUnUt2/fzlf822+/fety1KGnp8cnLsXFxWRjY0MH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\nYII=\n",
            "text/plain": [
              "<Figure size 936x216 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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/RKFeUFBATk5O4jX08PCgKVOm0JYtW2jLli3k4eEhru/iOE5SD7uQsvjgwYPN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\n",
            "text/plain": [
              "<Figure size 936x216 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "KIc0oqiD40HC"
      },
      "source": [
        "### Keras model\n",
        "If you are not sure what cross-entropy, dropout, softmax or batch-normalization mean, head here for a crash-course: [Tensorflow and deep learning without a PhD](https://github.com/GoogleCloudPlatform/tensorflow-without-a-phd/#featured-code-sample)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "56y8UNFQIVwj",
        "outputId": "e2fa4d89-ec5b-4508-950e-31ad0b87f09e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 391
        }
      },
      "source": [
        "model = tf.keras.Sequential(\n",
        "  [\n",
        "      tf.keras.layers.Reshape(input_shape=(28*28,), target_shape=(28, 28, 1)),\n",
        "      tf.keras.layers.Conv2D(kernel_size=3, filters=12, activation='relu', padding='same'),\n",
        "      tf.keras.layers.Conv2D(kernel_size=6, filters=24, activation='relu', padding='same', strides=2),\n",
        "      tf.keras.layers.Conv2D(kernel_size=6, filters=32, activation='relu', padding='same', strides=2),\n",
        "      tf.keras.layers.Flatten(),\n",
        "      tf.keras.layers.Dense(200, activation='relu'),\n",
        "      tf.keras.layers.Dense(10, activation='softmax')\n",
        "  ])\n",
        "\n",
        "model.compile(optimizer=tf.keras.optimizers.Adam(lr=0.01),\n",
        "              loss='categorical_crossentropy',\n",
        "              metrics=['accuracy'])\n",
        "\n",
        "# print model layers\n",
        "model.summary()\n",
        "\n",
        "# utility callback that displays training curves\n",
        "plot_training = PlotTraining(sample_rate=10, zoom=16)"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "reshape (Reshape)            (None, 28, 28, 1)         0         \n",
            "_________________________________________________________________\n",
            "conv2d (Conv2D)              (None, 28, 28, 12)        120       \n",
            "_________________________________________________________________\n",
            "conv2d_1 (Conv2D)            (None, 14, 14, 24)        10392     \n",
            "_________________________________________________________________\n",
            "conv2d_2 (Conv2D)            (None, 7, 7, 32)          27680     \n",
            "_________________________________________________________________\n",
            "flatten (Flatten)            (None, 1568)              0         \n",
            "_________________________________________________________________\n",
            "dense (Dense)                (None, 200)               313800    \n",
            "_________________________________________________________________\n",
            "dense_1 (Dense)              (None, 10)                2010      \n",
            "=================================================================\n",
            "Total params: 354,002\n",
            "Trainable params: 354,002\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "E0A7CSbW67EY",
        "colab_type": "text"
      },
      "source": [
        "### Learning Rate schedule"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2qz_k44U6_-f",
        "colab_type": "code",
        "outputId": "e996d4ec-36da-4f18-cb20-27d2ed451668",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 422
        }
      },
      "source": [
        "# lr decay function\n",
        "def lr_decay(epoch):\n",
        "  return 0.01 * math.pow(0.6, epoch)\n",
        "\n",
        "# lr schedule callback\n",
        "lr_decay_callback = tf.keras.callbacks.LearningRateScheduler(lr_decay, verbose=True)\n",
        "\n",
        "# important to see what you are doing\n",
        "plot_learning_rate(lr_decay, EPOCHS)"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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M/e63MePdN7T/Zm59FyWzZ8E7ciQ6W/b3+q/9nbX3A7DhnOf/iou3vIVT7/tlxu8ovvgi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\n",
            "text/plain": [
              "<Figure size 648x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "CuhDh8ao8VyB"
      },
      "source": [
        "### Train and validate the model"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "TTwH_P-ZJ_xx",
        "outputId": "e99eae66-946b-433f-bef1-886617b573d5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 466
        }
      },
      "source": [
        "steps_per_epoch = 60000//BATCH_SIZE  # 60,000 items in this dataset\n",
        "print(\"Steps per epoch: \", steps_per_epoch)\n",
        "\n",
        "history = model.fit(training_dataset, steps_per_epoch=steps_per_epoch, epochs=EPOCHS,\n",
        "                    validation_data=validation_dataset, validation_steps=1, callbacks=[plot_training, lr_decay_callback])"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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TpuGgT30SALD+xpvACyJGX3gBhXgCWqGA+f/+dUw74/SmPlPJSVj9H99BbM1a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ImTwXEtqJ7oEDxXG7Kc61uDUdKJOdwk+rgkxkf2QlywXuJN0Verc7PQ8mqXzlSCFU8sZZtqPdl5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\nKqb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PzZLEiVKl9WGtBqxTrKvi40eGRvQ6sKYsyI47sM7nOgaNM/1eP+B0DATJfsvy2I8k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\nYII=\n",
            "text/plain": [
              "<Figure size 1152x504 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r468/468 [==============================] - 4s 8ms/step - loss: 4.9380e-04 - acc: 0.9999 - val_loss: 0.0483 - val_acc: 0.9892\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "9jFVovcUUVs1"
      },
      "source": [
        "### Visualize predictions"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "w12OId8Mz7dF",
        "outputId": "7575d8a9-f707-4448-c161-617e93766c15",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 585
        }
      },
      "source": [
        "# recognize digits from local fonts\n",
        "probabilities = model.predict(font_digits, steps=1)\n",
        "predicted_labels = np.argmax(probabilities, axis=1)\n",
        "display_digits(font_digits, predicted_labels, font_labels, \"predictions from local fonts (bad predictions in red)\", N)\n",
        "\n",
        "# recognize validation digits\n",
        "probabilities = model.predict(validation_digits, steps=1)\n",
        "predicted_labels = np.argmax(probabilities, axis=1)\n",
        "display_top_unrecognized(validation_digits, predicted_labels, validation_labels, N, 7)"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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lqta+wtQXL++zw0eQ/fBvNOzeDSqlEqrCQsgtLCAzMEDKmbN4fu6C8H827/bD0z1/IPv+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\nRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 936x216 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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KSpB2MgzOM6dDt1EjGLd0QTN/v0rliHR1UZyVhfynCfxosa6xUY3aFjO3DrDu1xecSAQd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\nBoPBaIAwRZ3BYDAYDAaDwWiA/D9Vi1r/hQHPUQAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 936x216 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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PPze5HFM4cuQI1Go11Go1FAoF3N3dDT5E5nDlyhXhOkVERCAiIgJpaWmwsbFB69atkZub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\ng8FgMBgMRgvk/wHUq3fr+3Sc8QAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 936x216 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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1OI4TPUYdAFauXNmqo9u4cSMWL14MIhIM9ZMnT7Z7VKOurk7DSCciDSdRdXU1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\n",
            "text/plain": [
              "<Figure size 936x216 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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a51nOzs7uVjo9a2vrTo10Hx8feumll4QjPj6e8vPz6ebNm92pGhERLViw4ImL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\nHoAAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 936x216 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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Fra1tndfVajW8vb3h5OQkeBlUtVoNtVpdby7ypk2b4OzszH/PTk5OCAkJabZm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\nzdJAIo0AAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 936x216 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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Cr/2KL1y4gB07diAhIUF4UBMR1q9fb5DSqI+ysjL89NNPUKlU8Pb2hqenZw2LiaOjIxwd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\nAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 936x216 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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9vXVEkr29Pfbu3Yvnz5/rnHvt2jUMHTqUdRqrVq1qsv3MzEwm0quKx8zMTJ1QFzFso6nh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\nAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 936x216 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "SVY1pBg5ydH-"
      },
      "source": [
        "## License"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "hleIN5-pcr0N"
      },
      "source": [
        "\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "author: Martin Gorner<br>\n",
        "twitter: @martin_gorner\n",
        "\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "Copyright 2019 Google LLC\n",
        "\n",
        "Licensed under the Apache License, Version 2.0 (the \"License\");\n",
        "you may not use this file except in compliance with the License.\n",
        "You may obtain a copy of the License at\n",
        "\n",
        "    http://www.apache.org/licenses/LICENSE-2.0\n",
        "\n",
        "Unless required by applicable law or agreed to in writing, software\n",
        "distributed under the License is distributed on an \"AS IS\" BASIS,\n",
        "WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
        "See the License for the specific language governing permissions and\n",
        "limitations under the License.\n",
        "\n",
        "\n",
        "---\n",
        "\n",
        "\n",
        "This is not an official Google product but sample code provided for an educational purpose\n"
      ]
    }
  ]
}